Datasets:
jblitzar
/
github-python-corpus

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# log to syslog
import logging
from logging.handlers import SysLogHandler
syslog_handler = SysLogHandler()
syslog_handler.setLevel(logging.WARNING)
app.logger.addHandler(syslog_handler)
config = {
'development': DevelopmentConfig,
'testing': TestingConfig,
'production': ProductionConfig,
'heroku': HerokuConfig,
'unix': UnixConfig,
'default': DevelopmentConfig
}
# <FILESEP>
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from ast import arg
import logging
import os
from collections import deque
from typing import List
import time
import copy
import numpy as np
import torch
import wandb
from baselines import logger
from torch import nn
from level_replay.algo.dqn import init_
from level_replay import utils
from level_replay.algo.buffer import make_buffer, RolloutStorage
from level_replay.algo.policy import DQNAgent, ATCAgent
from level_replay.dqn_args import parser
from level_replay.envs import make_dqn_lr_venv
from level_replay.utils import ppo_normalise_reward, min_max_normalise_reward
from scipy.stats import skew, kurtosis
# os.environ["OMP_NUM_THREADS"] = "1"
# os.environ["WANDB_API_KEY"] = "anon"
# os.environ["WANDB_BASE_URL"] = "https://api.fairwandb.ai"
# os.environ["WANDB_API_KEY"] = "092a14187f6f01d8d2df67e8145ed4b16ba8bc9d"
def train(args, seeds):
args.cuda = not args.no_cuda and torch.cuda.is_available()
args.device = torch.device("cuda:0" if args.cuda else "cpu")
if "cuda" in args.device.type:
print("Using CUDA\n")
args.optimizer_parameters = {"lr": args.learning_rate, "eps": args.adam_eps}
args.seeds = seeds
args.sge_job_id = int(os.environ.get("JOB_ID", -1))
args.sge_task_id = int(os.environ.get("SGE_TASK_ID", -1))
args.PLR = False
for k, v in vars(args).items():
print(' ' * 26 + k + ': ' + str(v))
torch.set_num_threads(1)
utils.seed(args.seed)
name = (
f"dqn-{args.env_name}-{args.num_train_seeds}levels"
+ f"{'-PER' if args.PER else ''}"
+ f"{'-dueling' if args.dueling else ''}"
+ f"{'-qrdqn' if args.qrdqn else ''}"
+ f"{'-c51' if args.c51 else ''}"
+ f"{'-drq' if args.drq else ''}"
+ f"{'-autodrq' if args.autodrq else ''}"
+ f"{'-atc' if args.atc else ''}"
+ f"{'-seed' if args.seed else ''}"
+ '-' + args.exp_name
)
if not args.wandb:
os.environ["WANDB_MODE"] = "offline"
wandb.init(
# settings=wandb.Settings(start_method="fork"),
project="dqn_procgen",
entity="ydj",
name=name,
config=args,
# tags=["ddqn", "procgen"] + (args.wandb_tags.split(",") if args.wandb_tags else []),
group=None,
)